In fine-grained image recognition, the local area is also more important than the global structure. Similarly, for deepfake detection, local features are more effective than global features. If the local regions of the image are shuffled, the global structure of the image will be destroyed and the neural network will be forced to pay more attention to the distinguished area details  [1]}.
